Three-year ear, nose, and throat cross-sectional analysis of audiometric protocols for magnetic resonance imaging screening of acoustic tumors.

Objectives: (1) Evaluate audiometric protocols and recommend protocols with best sensitivity and specificity for magnetic resonance imaging (MRI) screening of acoustic tumors; (2) determine clinical risks (false negative) of missing acoustic tumors and potential wastes in screening (false positive) nonacoustic tumors or radiologically "normal" cases; and (3) identify the decibel difference and range of frequencies compared by the best-performing protocols.

Study Design: Cross-sectional study with chart review.

Setting: Ear, nose, and throat (ENT); audiology; and radiology departments in a tertiary-care hospital.

Modeling of human Heart Rate response during walking, cycling and rowing.

The aim of this paper is to study the human Heart Rate (HR) response during walking, cycling and rowing exercises using linear time varying (LTV) models. We used the frequency of exercise locomotion as the input to the model. This frequency characterizes the stride rate, cadence rate and strokes rate of the walking, cycling and rowing exercises respectively.

Model predictive control of relative blood volume and heart rate during hemodialysis.

To maintain the hemodynamic stability of patient undergoing hemodialysis, this article proposes a novel model-based control methodology to regulate the changes in relative blood volume (RBV) and percentage change in heart rate (DeltaHR(%)) during hemodialysis by adjusting the ultrafiltration rate (UFR). The control algorithm uses model predictive control (MPC) to account for system variability and to explicitly handle the constraints on UFR. Linear state-space system with time-varying parameters is introduced to model the RBV and DeltaHR.

Optimizing heart rate regulation for safe exercise.

Safe exercise protocols are critical for effective rehabilitation programs. This paper aims to develop a novel control strategy for an automated treadmill system to reduce the danger of injury during cardiac rehabilitation. We have developed a control-oriented nonparametric Hammerstein model for the control of heart rate during exercises by using support vector regression and correlation analysis.

Transient and steady state estimation of human oxygen uptake based on noninvasive portable sensor measurements.

The main motivation of this study is to establish an ambulatory cardio-respiratory analysis system for the monitoring and evaluation of exercise and regular daily physical activity. We explored the estimation of oxygen uptake by using noninvasive portable sensors. These sensors are easy to use but may suffer from malfunctions under free living environments.

Assessing the human cardiovascular response to moderate exercise: feature extraction by support vector regression.

This study aims to quantitatively describe the steady-state relationships among percentage changes in key central cardiovascular variables (i.e. stroke volume, heart rate (HR), total peripheral resistance and cardiac output), measured using non-invasive means, in response to moderate exercise, and the oxygen uptake rate, using a new nonlinear regression approach-support vector regression.

A robust control design for heart rate tracking during exercise.

In this study, a control design is proposed for the tracking control of heart rate response during treadmill exercise. The controller tracks an exerciser's heart rate to a given heart rate profile, that may represent a prescribed exercise protocol, by varying the speed of the treadmill. A guaranteed cost control approach is adopted in the control design so that the controller guarantees a certain level of performance.

Portable sensor based dynamic estimation of human oxygen uptake via nonlinear multivariable modelling.

Noninvasive portable sensors are becoming popular in biomedical engineering practice due to its ease of use. This paper investigates the estimation of human oxygen uptake (VO(2)) of treadmill exercises by using multiple portable sensors (wireless heart rate sensor and triaxial accelerometers). For this purpose, a multivariable Hammerstein model identification method is developed.

Nonlinear modeling and control of human heart rate response during exercise with various work load intensities.

The first objective of this paper is to introduce a nonlinear system to model the heart rate (HR) response during and after treadmill walking exercise. The model is a feedback interconnected system that has components to describe the central and peripheral local responses to exercise and their interactions. The parameters of the model were experimentally identified from subjects walking on a treadmill at different speeds.

A nonlinear dynamic model for heart rate response to treadmill walking exercise.

A dynamic model of the heart rate response to treadmill walking exercise is presented. The model is a feedback interconnected system; the subsystem in the forward path represents the neural response to exercise, while the subsystem in the feedback path describes the peripheral local response. The parameters of the model were estimated from 5 healthy adult male subjects, each undertaking 3 sets of walking exercise at different speeds.

Nonparametric Hammerstein model based model predictive control for heart rate regulation.

This paper proposed a novel nonparametric model based model predictive control approach for the regulation of heart rate during treadmill exercise. As the model structure of human cardiovascular system is often hard to determine, nonparametric modelling is a more realistic manner to describe complex behaviours of cardiovascular system. This paper presents a new nonparametric Hammerstein model identification approach for heart rate response modelling.